Conventionally, image data has been represented by image feature data indicative of its feature, and this image feature data has been used to determine similarities in respective images. Also, apparatuses and computer programs have been developed for retrieving similar images (for example, from stored images). A method typically employed in such conventional image search techniques uses feature data which represents colors included in an image and a structure possessed by the image (hereinafter referred to as color structure feature data) to retrieve similar images from similarities in the features.
Exemplary prior art techniques for representing a chromatic feature and a structural feature possessed by an image are disclosed in JP-A-11-316819 and JP-A-2000-259832.
JP-A-11-316819 proposes a method which divides an image into a plurality of blocks, calculates a histogram for colors included in each block, defines a collection of values of the color histogram in each block as color distribution feature data, and uses the color distribution feature data to determinate similarities and searches. In this color distribution feature data, since the color histogram is indicated on a block-by-block basis, the chromatic feature and structural feature possessed by the image can be reflected to the determination of similarities.
JP-A-2000-259832 discloses an image search technique which utilizes frequency distribution feature data, which represents a color structure possessed by an image in the frequency domain, as image feature data. The frequency distribution feature data of an image refers to image feature data which represents the energy in each band that is found by dividing a frequency distribution of the spectrum of colors (average color) in the image into a plurality of bands, and analyzing each of the bands in terms of frequency.
FIG. 1 is a block diagram illustrating the configuration of a main portion of an image search system described in JP-A-2000-259832. This image search system comprises image feature data generating unit 102 for generating frequency distribution feature data 103 from input image data 101; frequency distribution feature data storage unit 104 for previously storing therein frequency distribution feature data of images to be searched; and similarity calculating unit 106 for calculating similarity 107 using frequency distribution feature data 104 of the input image and feature data 105 stored in frequency distribution feature data storage unit 104.
Image feature data generating unit 102 comprises reduced image generating means 110 for generating reduced image 111 from image data 101; frequency analyzing means 112 for performing a frequency analysis on generated reduced image 111; and DC component and partial AC component extracting means 114 for extracting a DC component and part of AC components from among orthogonal conversion coefficients 113 derived from frequency analyzing means 112 as frequency distribution feature data 103.
The foregoing image search system fails to extract color distribution feature data and frequency distribution feature data from an image having an arbitrary shape-because these feature data are extracted on the assumption that the image is rectangular. For this reason, this system cannot conduct an image search in an image database which mixedly stores images having various shapes.